Fuzzy classification combined with spatial prediction was used to assess the state of soil pollution in the peri-urban Beijing area. Total concentrations of As, Cr, Cd, Hg, and Pb were determined in 220 topsoil sample...Fuzzy classification combined with spatial prediction was used to assess the state of soil pollution in the peri-urban Beijing area. Total concentrations of As, Cr, Cd, Hg, and Pb were determined in 220 topsoil samples (0-20 cm) collected using a grid design in a study area of 2600 km2. Heavy metal concentrations were grouped into three classes according to the optimum number of classes and fuzziness exponent using the fuzzy c-mean (FCM) algorithm. Membership values were interpolated using ordinary kriging. The polluted soils of the study area induced by the measured heavy metals were concentrated in the northwest corner and eastern part, especially the southeastern part close to the urban zone, whereas the soils free of pollution were mainly distributed in the southwestern part. The soils with potential risk of heavy metal pollution were located in isolated spots mainly in the northern part and southeastern corner of the study region. The FCM algorithm combined with geostatistical techniques, as compared to conventional single geostatistical kriging methods, could produce a prediction with a quantitative uncertainty evaluation and higher reliability. Successful prediction of soil pollution achieved with FCM algorithm in this study indicated that fuzzy set theory had great potential for use in other areas of soil science.展开更多
A SOTER-based automatic procedure for qualitative land evaluation is developed. This procedure was created in the automated land evaluation system (ALES). The objective was to design a procedure that allows for a quic...A SOTER-based automatic procedure for qualitative land evaluation is developed. This procedure was created in the automated land evaluation system (ALES). The objective was to design a procedure that allows for a quick separation of potentially suitable from non-suitable SOTER units for the intended land use, indicating constraints to different kinds of land use. Different kinds of land are unequal1y suited to various uses, land eva1uation is the assessment of the suitability of a tract of land for a specified kind of land use. In practice this implicates the comparison (matching) between the requirements of a specified land use and the properties of the land. Land evaluation concepts and definitions are treated in the paper. The ALES is a computer program that allows land evaluators to build their own knowledge-based system with which they can compute the physical and economical suitability of map units in accordance with FAO framework for land evaluation. The ALES program works with so-called decision trees, being hierarchical multiway keys in which the leaves are results (e.g., severity levels of land qualities), and the interior nodes of the tree are decision criteria (e.g., land characteristic values). These trees are traversed by the program to compute an evaluation using actual land data for each map unit. SOTAL is a SOTER-based qualitative model developed in ALES for physical land evaluation in which presently three land utilization types (LUTs) are distinguished, i.e., cultivated banana, coffee and rubber under different input and technological conditions. These LUTs are characterized by 11 landuse requirements and evaluated by matching the land use requirements with the corresponding land qualities. The paper elaborates on the criteria used in SOTAL for land quality assessment and how a final suitability rating is achieved on the basis of the rated land qualities. Results are visualized through G1S-generated maps as products in response to the specific information and data needs of decision and policy makers.展开更多
基金Project supported by the National Natural Science Foundation of China (Nos. 40571065 and 40235054)the National Key Basic Research Support Foundation of China (No. G1999045707).
文摘Fuzzy classification combined with spatial prediction was used to assess the state of soil pollution in the peri-urban Beijing area. Total concentrations of As, Cr, Cd, Hg, and Pb were determined in 220 topsoil samples (0-20 cm) collected using a grid design in a study area of 2600 km2. Heavy metal concentrations were grouped into three classes according to the optimum number of classes and fuzziness exponent using the fuzzy c-mean (FCM) algorithm. Membership values were interpolated using ordinary kriging. The polluted soils of the study area induced by the measured heavy metals were concentrated in the northwest corner and eastern part, especially the southeastern part close to the urban zone, whereas the soils free of pollution were mainly distributed in the southwestern part. The soils with potential risk of heavy metal pollution were located in isolated spots mainly in the northern part and southeastern corner of the study region. The FCM algorithm combined with geostatistical techniques, as compared to conventional single geostatistical kriging methods, could produce a prediction with a quantitative uncertainty evaluation and higher reliability. Successful prediction of soil pollution achieved with FCM algorithm in this study indicated that fuzzy set theory had great potential for use in other areas of soil science.
基金UNDP Project CPR/96/105 "Sustainable Land Management for Agricultural Production in Hainan Province"
文摘A SOTER-based automatic procedure for qualitative land evaluation is developed. This procedure was created in the automated land evaluation system (ALES). The objective was to design a procedure that allows for a quick separation of potentially suitable from non-suitable SOTER units for the intended land use, indicating constraints to different kinds of land use. Different kinds of land are unequal1y suited to various uses, land eva1uation is the assessment of the suitability of a tract of land for a specified kind of land use. In practice this implicates the comparison (matching) between the requirements of a specified land use and the properties of the land. Land evaluation concepts and definitions are treated in the paper. The ALES is a computer program that allows land evaluators to build their own knowledge-based system with which they can compute the physical and economical suitability of map units in accordance with FAO framework for land evaluation. The ALES program works with so-called decision trees, being hierarchical multiway keys in which the leaves are results (e.g., severity levels of land qualities), and the interior nodes of the tree are decision criteria (e.g., land characteristic values). These trees are traversed by the program to compute an evaluation using actual land data for each map unit. SOTAL is a SOTER-based qualitative model developed in ALES for physical land evaluation in which presently three land utilization types (LUTs) are distinguished, i.e., cultivated banana, coffee and rubber under different input and technological conditions. These LUTs are characterized by 11 landuse requirements and evaluated by matching the land use requirements with the corresponding land qualities. The paper elaborates on the criteria used in SOTAL for land quality assessment and how a final suitability rating is achieved on the basis of the rated land qualities. Results are visualized through G1S-generated maps as products in response to the specific information and data needs of decision and policy makers.
